<i>mzGroupAnalyzer</i> is able to detect possible metabolic steps out of various proposed sum formulas for a measured <i>m/z</i> feature.

<p><b>A</b> Kaempferol and Quercetin standards measured by LC-MS result into several sum formula suggestions for the measured mass-to-charge-ratio (<i>m/z</i>). Because a low ppm deviation of assigned elemental composition to the mass is not the decisive factor, the correct sum formula might not be the first one proposed and thus several must be looked at, which is handled by the program automatically. If <i>mzGroupAnalyzer</i> finds a possible reaction step (out of a list of reactions which can be altered manually), it is reported to the user. <b>B</b> MS² spectra of Kaempferol (left) and Quercetin (right). The fragmentation schemes are in accordance with published literature <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-March1" target="_blank">[42]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-AbadGarcia1" target="_blank">[43]</a>. The difference of one oxygen atom (nominal mass 16) is visible in the fragments <i>m/z</i> 213→229 and 241→257, while <i>m/z</i> 165 occurs in both product scans.</p

After oxidative stress the <i>Arabidopsis thaliana</i> plants turn from green into purple indicating a dramatic shift in metabolism, specifically elevated flavonoid biosynthesis involved in oxidative stress protection [6].

<p><b>A</b> Plants turns from green to purple under high light and cold temperature treatment. <b>B</b> Van Krevelen diagram of the most abundant <i>m/z</i> values of unstressed (green dots) and 20-day cold stressed (purple dots) Arabidopsis plants. A clear shift of metabolism in the stressed plants is visible.</p

Structure validation of <i>m/z</i> 1121 by MS³ product ion scans.

<p>Both MS² fragments <i>m/z</i> 535 and 873 result in the core cyanidin structure by undergoing MS³ fragmentation. <i>m/z</i> 1077, the putatively decarboxylized form of 1121, yields <i>m/z</i> 491, as observed in the MS² spectrum already, by scission of the 3-O-glycosidic bond. Fragment <i>m/z</i> 873 arises again from the breaking of the glycosidic bond at 5-O. <i>m/z</i> 1017 would comply with the complete removal of the rest of the former malonyl group together with a water loss (−60 u). A putative structure is given.</p

Identification of biochemical transformations of <i>in vivo</i> data using <i>mzGroupAnalyzer</i>.

<p>A metabolic pathway leading to a putative new compound <i>m/z</i> 1121 is revealed. Amongst several hundreds of other interlinked <i>m/z</i> values in the data, the figure shows metabolic transitions derived from sub-ppm accuracy measurements on the left side and their corresponding MS² product ion scans on the right. Comparison of the spectral information from step to step reveals the possible location of metabolic structural changes. Stereochemistry is assumed due to literature findings <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-Tohge1" target="_blank">[33]</a>.</p

<i>mzGroupAnalyzer</i>-Predicting Pathways and Novel Chemical Structures from Untargeted High-Throughput Metabolomics Data

<div><p>The metabolome is a highly dynamic entity and the final readout of the genotype x environment x phenotype (GxExP) relationship of an organism. Monitoring metabolite dynamics over time thus theoretically encrypts the whole range of possible chemical and biochemical transformations of small molecules involved in metabolism. The bottleneck is, however, the sheer number of unidentified structures in these samples. This represents the next challenge for metabolomics technology and is comparable with genome sequencing 30 years ago. At the same time it is impossible to handle the amount of data involved in a metabolomics analysis manually. Algorithms are therefore imperative to allow for automated <i>m/z</i> feature extraction and subsequent structure or pathway assignment. Here we provide an automated pathway inference strategy comprising measurements of metabolome time series using LC- MS with high resolution and high mass accuracy. An algorithm was developed, called <i>mzGroupAnalyzer</i>, to automatically explore the metabolome for the detection of metabolite transformations caused by biochemical or chemical modifications. Pathways are extracted directly from the data and putative novel structures can be identified. The detected <i>m/z</i> features can be mapped on a van Krevelen diagram according to their H/C and O/C ratios for pattern recognition and to visualize oxidative processes and biochemical transformations. This method was applied to <i>Arabidopsis thaliana</i> treated simultaneously with cold and high light. Due to a protective antioxidant response the plants turn from green to purple color via the accumulation of flavonoid structures. The detection of potential biochemical pathways resulted in 15 putatively new compounds involved in the flavonoid-pathway. These compounds were further validated by product ion spectra from the same data. The <i>mzGroupAnalyzer</i> is implemented in the graphical user interface (GUI) of the metabolomics toolbox COVAIN (Sun & Weckwerth, 2012, Metabolomics 8: 81–93). The strategy can be extended to any biological system.</p></div

A proposed network of the detected anthocyanin family featuring putatively novel compounds as well as known structures including the KEGG pathway of anthocyanin biosynthesis [38], [44].

<p>Only compounds from the KEGG anthocyanin pathway are depicted, for which a suitable precursor mass was found in the data. Exact masses, sum formulas, and main MS² fragments of the new compounds are compiled in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone-0096188-t001" target="_blank">Table 1</a>; reconstructed structures together with MS² scans are in the supporting information. The network was created with VANTED <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-Junker1" target="_blank">[45]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-Rohn1" target="_blank">[46]</a>.</p

Exploration of the van Krevelen diagram created by sum formulas with chemical transformations detected by <i>mzGroupAnalyzer</i>.

<p><b>A </b><i>m/z</i> 1181, 1195, 1197 and 1211 are interconnected with net shifts of ½ O₂ and a CH₂ group and form a rhombic pattern. <b>B</b> Proposed fragmentation scheme of these compounds under the chosen conditions. <b>C</b> Product ion scans show similar fragmentation behavior of the polysubstituted anthocyanins. The spectrum of <i>m/z</i> 1195 shows a peak at <i>m/z</i> 549, pointing to a methyl group at the cyanidin core. A putative methylation site is shown.</p

Putative compounds including their <i>mzGroupAnalyzer</i>- predicted sum formulas, the corresponding exact mass as well as dominant MS² product ion fragments.

<p>The nomenclature is according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-Tohge1" target="_blank">[33]</a>. Compounds <i>m/z</i> 1125, 1197 and 1211 were found in <i>Matthiola incana</i> by <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-Saito1" target="_blank">[39]</a>.</p

Scheme of the <i>mzGroupAnalyzer</i> and <i>Pathway Viewer</i> algorithm and GUI implementation.

<p>The program reads the <i>m/z</i> features which are extracted from Xcalibur, as well as the user predefined reaction rules. Then it finds transformations between all pairs of <i>m/z</i> features, and reports the frequency of transformations for the listed and not listed but potentially existing rules. Next, the program starts searching pathways inside the <i>m/z</i> features' network. A shorter path existing in other longer paths is removed, thereby non-redundant pathways are obtained. Then, <i>mzGroupAnalyzer</i> opens the Pathway Viewer, in which pathways satisfying user-defined filtering options will be displayed on the panel. The pathway diagram, which consists of reaction rules, <i>m/z</i> feature names, compositions and time points, can be plotted by clicking the table. Finally, all the results, including the frequency table of transformations, the interconnected network visualization file (in Pajek's format), the inferred pathways and a Matlab workspace (suffixed with mzStruct.mat) containing all results, will be exported to the user-specified folder.</p